Staff characteristics associated with nursing home residents’ initial transfer to emergency care facilities– a nationwide cohort study in Norway

Abstract Background Transfers from nursing homes (NHs) to emergency care facilities (ECFs) are often questioned, as many residents are terminally ill and may have access to on-site qualified care from staff. We sought to investigate the association between nursing home staff characteristics (e.g., time since graduation, turnover, sick leave) and residents’ risk of a first acute care transfer after accounting for the competing risk of resident mortality. Methods A semi-Markov irreversible illness-death model was used to assess the association between NH staff characteristics and residents’ risk of initial ECF transfer in a retrospective, register-based longitudinal cohort study. Analyses were stratified by NH resident sex. Resident age, comorbidity, NH number of residents (occupancy), and proximity of next of-kin were used as additional predictors in the model. Data on staff characteristics at 851 NHs between 2016 and 2022 were linked to each resident’s NH admission date. Data on NH staff and residents was obtained from Statistics Norway (SSB), the Norwegian Registry for Primary Health Care (NRPHC), the Norwegian Control and Payment of Health Reimbursements Database (KUHR), and the Norwegian Patient Registry (NPR). Results Analyses were conducted on 76,140 NH residents, aged 65 and older, who entered long-term care in Norway between 2017 and 2022, of whom 46% ( n = 34,899) underwent an emergency transfer to an ECF, and 66% ( n = 50,548) died before the end of follow-up on 2022-12-31. Residents had a lower estimated ECF transfer risk in NHs where staff had more experience (longer average time since graduation). Specifically, for every additional decade of NH staff time since graduation, the estimated hazard ratio was 0.95 [95% CI: 0.93–0.98, p < 0.001] for males and 0.94 [95% CI: 0.91–0.97, p < 0.001] for females. Female residents had a higher estimated risk of transfer in NHs that had higher staff turnover rates, with an estimated hazard ratio of 1.01 [95% CI: 1.00–1.03, p = 0.035] for each additional increase of 10% points of yearly turnover. NH staff sick leave was not statistically significantly associated with transfer risk for either reported sex. Conclusions Higher average staff experience in nursing homes is associated with a reduced risk of residents’ initial transfer to emergency care facilities. Accumulated knowledge among NH staff and acute care decision outcomes should be further investigated, and this study underscores the need for NH administrators and policymakers to prioritize staff retention.

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Journal
BMC Health Services Research
Published
2026-09-30
DOI
https://doi.org/10.1186/s12913-026-15748-9
Primary Topic
Geriatric Care and Nursing Homes
Type
article
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article

Staff characteristics associated with nursing home residents’ initial transfer to emergency care facilities– a nationwide cohort study in Norway

Oddvar Førland, Karl Ove Hufthammer, Arne Bastian Wiik, Malcolm Bray Doupe
BMC Health Services Research
Geriatric Care and Nursing Homes
article

Staff characteristics associated with nursing home residents’ initial transfer to emergency care facilities– a nationwide cohort study in Norway

Oddvar Førland, Karl Ove Hufthammer, Arne Bastian Wiik, Malcolm Bray Doupe
article en

Abstract

Abstract Background Transfers from nursing homes (NHs) to emergency care facilities (ECFs) are often questioned, as many residents are terminally ill and may have access to on-site qualified care from staff. We sought to investigate the association between nursing home staff characteristics (e.g., time since graduation, turnover, sick leave) and residents’ risk of a first acute care transfer after accounting for the competing risk of resident mortality. Methods A semi-Markov irreversible illness-death model was used to assess the association between NH staff characteristics and residents’ risk of initial ECF transfer in a retrospective, register-based longitudinal cohort study. Analyses were stratified by NH resident sex. Resident age, comorbidity, NH number of residents (occupancy), and proximity of next of-kin were used as additional predictors in the model. Data on staff characteristics at 851 NHs between 2016 and 2022 were linked to each resident’s NH admission date. Data on NH staff and residents was obtained from Statistics Norway (SSB), the Norwegian Registry for Primary Health Care (NRPHC), the Norwegian Control and Payment of Health Reimbursements Database (KUHR), and the Norwegian Patient Registry (NPR). Results Analyses were conducted on 76,140 NH residents, aged 65 and older, who entered long-term care in Norway between 2017 and 2022, of whom 46% ( n = 34,899) underwent an emergency transfer to an ECF, and 66% ( n = 50,548) died before the end of follow-up on 2022-12-31. Residents had a lower estimated ECF transfer risk in NHs where staff had more experience (longer average time since graduation). Specifically, for every additional decade of NH staff time since graduation, the estimated hazard ratio was 0.95 [95% CI: 0.93–0.98, p < 0.001] for males and 0.94 [95% CI: 0.91–0.97, p < 0.001] for females. Female residents had a higher estimated risk of transfer in NHs that had higher staff turnover rates, with an estimated hazard ratio of 1.01 [95% CI: 1.00–1.03, p = 0.035] for each additional increase of 10% points of yearly turnover. NH staff sick leave was not statistically significantly associated with transfer risk for either reported sex. Conclusions Higher average staff experience in nursing homes is associated with a reduced risk of residents’ initial transfer to emergency care facilities. Accumulated knowledge among NH staff and acute care decision outcomes should be further investigated, and this study underscores the need for NH administrators and policymakers to prioritize staff retention.

BMC Health Services Research
Western Norway University of Applied Sciences (NO), University of Manitoba (CA)
Good health and well-being
Openalex Percentile: Top 7%
Geriatric Care and Nursing Homes
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